coursemapLoading course
Rsch Sch of Finance, Actuarial Studies & App Stats · ANU College of Business and Economics
Quantitative Research Methods provides training in the gathering, description and analysis of quantitative information in a broad range of different disciplines including, science, arts, sports, business, management and the financial sciences. Further, students use the skills acquired in this course to identify problems, interpret and analyse results, and provide solutions while engaging with external stakeholders. This is a course in research methods including discussions, analysis, interpretation and providing solutions of: data gathering issues and techniques; sources of data and potential biases; graphical and numerical data description techniques including simple linear regression, sampling behaviour of averages and the Central Limit Theorem; point and interval estimation procedures; concepts in hypothesis testing for comparing two populations, simple and multiple linear regression; p-values and significance levels. Students in this course are exposed to a variety of different problems/issues from different disciplines and seek to provide input to these problems through the application of quantitative data analysis skills. The data sets and/or problems/issues are introduced through a variety of guest speakers that are included in the class, as well as a series of recordings, blogs or newspaper articles to drive and contextualise the data stemming from the variety of different disciplines.
The research-based assessment will consist of assignments, providing students with a confined set of datasets along with a pertinent problem from the particular discipline that the dataset is relevant to. The objective of this assessment is to work collaboratively in groups to analyse and draw meaningful conclusions from data presented in graphical format. In this task, students will demonstrate in groups their ability to extract key information from data and communicate findings in a short, in-person oral group presentation.
Learning outcomes 1, 2, 3, 4
The other assessment may include but is not restricted to: exams, quizzes, presentations and other assessments as appropriate.
Learning outcomes 1, 2, 3, 4, 5, 6, 7
Students are expected to commit at least 10 hours per week to completing the work in this course. This will include at least 3 contact hours per week and up to 7 hours of private study time.
Information about the prescribed textbook will be available via the class summary.